The growth of the Internet has allowed people from all parts of the world to communicate with each other at a rapid pace. This capacity for immense sharing of knowledge has led to the creation of websites devoted to enabling people to tap into the expertise of others in ways never before imagined. These knowledge-sharing social sites are designed to allow users to ask questions and receive answers from other users.
A drawback to the wide availability of users able to post answers to questions is the increased amount of noise to signal; that is, the more answers posted to a question, the greater the amount of uninformed guesses, banter, and otherwise irrelevant user contributions that must be waded through in order to find quality responses.
For example, in response to a question about automobile repair, there may be one hundred responses, or “answers”. Of these one hundred answers, if only ten percent are worthwhile, that means a user must read 90 answers that either give wrong information, no information, or incomplete information. The more difficult it becomes for a user to find quality answers to her questions, the less likely the user is to frequent the web site. If this occurs on a large enough scale, then fewer users will visit the website, thereby reducing the audience available to answer questions and lessening the scope of knowledge.
One approach to filtering out lower-quality answers is human interaction. Humans may read answers and manually remove or identify answers that are deemed uninformative. A drawback to this approach is that it is time- and labor-intensive, and requires a large number of people to continuously monitor answers. Also, human moderation of answers may be prone to personal biases, either about what is considered an “appropriate” answer to a question in a particular subject or about the individual answering the question.
Therefore, an approach for determining the quality of posts on a web site or message board, which does not experience the disadvantages of the above approaches, is desirable. The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.